Validation of the APACHE IV model and its comparison with the APACHE II, SAPS 3, and Korean SAPS 3 models for the prediction of hospital mortality in a Korean surgical intensive care unit

Objective: Assess for continued improvements in patient outcomes after updating our institutional sedation and analgesia protocol to include recommendations from the 2013 Society of Critical Care Medicine (SCCM) Pain, Agitation, and Delirium (PAD) guidelines. Methods: Retrospective before-and-after study in a mixed medical/surgical intensive care unit (ICU) at an academic medical center. Mechanically ventilated adults admitted from September 1, 2011 through August 31, 2012 (pre-implementation) and October 1, 2012 through September 30, 2017 (post-implementation) were included. Measurements included number of mechanically ventilated patients, APACHE IV scores, age, type of patient (medical or surgical), admission diagnosis, ICU length of stay (LOS), hospital LOS, ventilator days, number of self-extubations, ICU mortality, ICU standardized mortality ratio, hospital mortality, hospital standardized mortality ratio, medication data including as needed (PRN) analgesic and sedative use, and analgesic and sedative infusions, and institutional savings. Results: Ventilator days (Pre-PAD = 4.0 vs. Year 5 post = 3.2, P < .0001), ICU LOS (Pre-PAD = 4.8 days vs. Year 5 post = 4.1 days, P = .0004) and hospital LOS (Pre-PAD = 14 days vs. Year 5 post = 12 days, P < .0001) decreased after protocol implementation. Hospital standardized mortality ratio (Pre-PAD = 0.69 vs. Year 5 post = 0.66) remained constant; while, APACHE IV scores (Pre-PAD = 77 vs. Year 5 post = 89, P < .0001) and number of intubated patients (Pre-PAD = 1146 vs. Year 5 post = 1468) increased over the study period. Using the decreased ICU and hospital LOS estimates, it is projected the institution saved $4.3 million over the 5 years since implementation. Conclusions: Implementation of an updated PAD protocol in a mixed medical/surgical ICU was associated with a significant decrease in ventilator time, ICU LOS, and hospital LOS without a change in the standardized mortality ratio over a five-year period. These favorable outcomes are associated with a significant cost savings for the institution.

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Timing of Admission to the Surgical Intensive Care Unit is Associated with in-Hospital Mortality

10.21203/rs.3.rs-154631/v1 ◽

2021 ◽

Author(s):

Mi Kyoung Kim ◽

Eun-Joo Jung ◽

Seulkee Park ◽

Im-kyung Kim

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Hospital Mortality ◽

Outcome Measurement ◽

Work Hours ◽

Surgical Intensive Care Unit ◽

Surgical Intensive Care ◽

After Hours ◽

The Times ◽

Unplanned Admissions

Abstract Background: Knowledge about the relationship between timing of admission to the intensive care unit (ICU) and mortality among surgical patients admitted for acute care is limited.Objective: We aimed to investigate whether admission to the surgical intensive care unit (SICU) during after-hours (all the times when intensivists were not staffed in the ICU) was associated with in-hospital mortality.Methods: This retrospective cohort study was conducted at a tertiary academic hospital, in which we analyzed data of 571 patients admitted to the SICU whose complete medical records were available. The work-hours were defined as 07:00-19:00 from Monday to Friday during which intensivists were staffed in the ICU. The after-hours were defined as all other times during which intensivists were not staffed in the SICU. The primary outcome measurement was in-hospital mortality according to the time of SICU admission.Results: In all, 333 and 238 patients were admitted to the SICU during work-hours and after-hours, respectively. Unplanned admissions (33.3% vs. 47.1%, p<0.001), Acute Physiology and Chronic Health Evaluation II score ≥25 (11.1% vs. 23.9%, p<0.001), ventilator support (17.4% vs. 34.0%, p<0.001), and use of inotropics (33.3% vs. 50.0%, p<0.001) were significantly higher in the after-hours group than in the work-hours group. In the multivariate analyses of the association between the time of SICU admission and in-hospital mortality, the timing of SICU admission was an independent factor for in-hospital mortality (OR=2.526; 95% CI=1.010-6.320, p=0.048). Conclusions: In this study, we found that admission to the SICU during after-hours was associated with increased in-hospital mortality.

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Data Science for Extubation Prediction and Value of Information in Surgical Intensive Care Unit

Journal of Clinical Medicine ◽

10.3390/jcm8101709 ◽

2019 ◽

Vol 8 (10) ◽

pp. 1709 ◽

Cited By ~ 3

Author(s):

Tsung-Lun Tsai ◽

Min-Hsin Huang ◽

Chia-Yen Lee ◽

Wu-Wei Lai

Keyword(s):

Intensive Care Unit ◽

Logistic Regression ◽

Intensive Care ◽

Prediction Model ◽

Value Of Information ◽

Data Science ◽

Apache Ii ◽

Surgical Intensive Care Unit ◽

Surgical Intensive Care ◽

Science Framework

Besides the traditional indices such as biochemistry, arterial blood gas, rapid shallow breathing index (RSBI), acute physiology and chronic health evaluation (APACHE) II score, this study suggests a data science framework for extubation prediction in the surgical intensive care unit (SICU) and investigates the value of the information our prediction model provides. A data science framework including variable selection (e.g., multivariate adaptive regression splines, stepwise logistic regression and random forest), prediction models (e.g., support vector machine, boosting logistic regression and backpropagation neural network (BPN)) and decision analysis (e.g., Bayesian method) is proposed to identify the important variables and support the extubation decision. An empirical study of a leading hospital in Taiwan in 2015–2016 is conducted to validate the proposed framework. The results show that APACHE II and white blood cells (WBC) are the two most critical variables, and then the priority sequence is eye opening, heart rate, glucose, sodium and hematocrit. BPN with selected variables shows better prediction performance (sensitivity: 0.830; specificity: 0.890; accuracy 0.860) than that with APACHE II or RSBI. The value of information is further investigated and shows that the expected value of experimentation (EVE), 0.652 days (patient staying in the ICU), is saved when comparing with current clinical experience. Furthermore, the maximal value of information occurs in a failure rate around 7.1% and it reveals the “best applicable condition” of the proposed prediction model. The results validate the decision quality and useful information provided by our predicted model.

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Evaluation of the consistency of Acute Physiology and Chronic Health Evaluation (APACHE II) scoring in a surgical intensive care unit

Critical Care Medicine ◽

10.1097/00003246-199212000-00014 ◽

1992 ◽

Vol 20 (12) ◽

pp. 1681-1687 ◽

Cited By ~ 39

Author(s):

METTE M. BERGER ◽

ALFIO MARAZZI ◽

JAMES FREEMAN ◽

RENÉ CHIOLÉRO

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Chronic Health Evaluation ◽

Apache Ii ◽

Surgical Intensive Care Unit ◽

Health Evaluation ◽

Surgical Intensive Care ◽

Chronic Health

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Validation of a severity of illness score (APACHE II) in a surgical intensive care unit

Intensive Care Medicine ◽

10.1007/bf00273563 ◽

1989 ◽

Vol 15 (8) ◽

pp. 519-522 ◽

Cited By ~ 49

Author(s):

G. Giangiuliani ◽

A. Mancini ◽

D. Gui

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Severity Of Illness ◽

Apache Ii ◽

Surgical Intensive Care Unit ◽

Surgical Intensive Care ◽

Score Apache

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AN ICD-9 BASED ILLNESS SEVERITY SCORE (ICISS) OUT PERFORMS APACHE II IN PREDICTING SURVIVAL, HOSPITAL CHARGES AND LENGTH OF STAY IN SURGICAL INTENSIVE CARE UNIT PATIENTS

Critical Care Medicine ◽

10.1097/00003246-199801001-00013 ◽

1998 ◽

Vol 26 (Supplement) ◽

pp. 25A ◽

Cited By ~ 2

Author(s):

Toan Huynh ◽

Jeff Guy ◽

Robert Rutledge

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Length Of Stay ◽

Severity Score ◽

Illness Severity ◽

Apache Ii ◽

Hospital Charges ◽

Surgical Intensive Care Unit ◽

Surgical Intensive Care ◽

Illness Severity Score

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Obesity Does Not Affect Mortality after Trauma

The American Surgeon ◽

10.1177/000313480607201028 ◽

2006 ◽

Vol 72 (10) ◽

pp. 966-969 ◽

Cited By ~ 9

Author(s):

Rodrigo F. Alban ◽

Sergey Lyass ◽

Daniel R. Margulies ◽

M. Michael Shabot

Keyword(s):

Intensive Care Unit ◽

Risk Factor ◽

Intensive Care ◽

Adverse Outcomes ◽

Apache Ii ◽

Surgical Intensive Care Unit ◽

Apache Ii Score ◽

Surgical Intensive Care ◽

Significant Difference ◽

Nonobese Patients

Although obesity has been proposed as a risk factor for adverse outcomes after trauma, numerous studies report conflicting results. The objective of this study was to compare outcomes of obese and nonobese patients after trauma. The study population consisted of all trauma patients admitted to a surgical intensive care unit in a Level I trauma center from January 1999 to December 2002. Admission data, demographics, injury severity score (ISS), severity of illness, hospital course, complications, and outcomes were compared between obese (OB; body mass index [BMI] ≥ 30), and nonobese patients (NOB; BMI ≤ 29). A total of 918 patients was included in the study, 135 OB (14.7%) and 783 NOB (85.3%). There was no significant difference in demographic data, ISS, APACHE II score, and hospital stay. Intensive care unit stay was longer for OB patients (6.8 vs 4.8 days, P = 0.04). Overall mortality was 5.9 per cent for OB and 8.0 per cent for NOB patients (P = 0.48). Mortality by mechanism of injury was 3.4 per cent OB versus 7.4 per cent NOB (P = 0.26) for blunt and 10.6 per cent OB versus 10.2 per cent NOB (P = 0.9) for penetrating injury. The three most common complications associated with death were pulmonary, cardiovascular, and neurological deterioration. Using logistic regression analysis, age and ISS and APACHE II scores were associated with mortality, but BMI was not. We conclude that obesity does not appear to be a risk factor for adverse outcomes after blunt or penetrating trauma. Further research is warranted to uncover the reason for discrepant findings between centers.

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